This is the blog of David M. Raab, marketing technology consultant and analyst. Mr. Raab is Principal at Raab Associates Inc. The blog is named for the Customer Experience Matrix, a tool to visualize marketing and operational interactions between a company and its customers.

The paper describes a fundamental contrast between a “center out” model of data usage favored by IT (carefully and centrally controlled) and an “edge based” model favored by business analysts, who act as independent data “hunter-gatherers” to combine and use data in ways that the central resources are not designed to support. Devlin's term for this is “emergent prototyping”, a trial-and-error process of reworking an analysis until it produces something useful.

He also suggests that analysts work first by themselves, and then, if they find something interesting, share it with other analysts. Only later, when something seems really important and reusable, will they try to get corporate IT to add it to the central systems.

My own mental model is slightly different. I see analysts as spending very little time gathering data. In practice, most of what they need resides in corporate systems, so analysts are largely at the mercy of IT to provide extracts of required sources. Although waiting for those extracts is probably the biggest constraint on what analysts can accomplish, they don't spend that time twiddling their thumbs. Most of their work day (apart from meetings, etc.) is spent manipulating and interpreting data, and, as Devlin suggests, discussing results with other analysts.

This difference in perspective has some impact on judging what matters in a business analysis tool. If data gathering is really important, then features for extraction and consolidation are critical. If manipulation and interpretation matter most, then features for processing and visualization are at the top of the list.

As I recall, Lyza doesn’t offer particularly advanced extraction or consolidation features (e.g. fuzzy matching), so this isn’t necessarily a topic they should stress. Lyzasoft might disagree – and I’ll gladly concede that the system allows basic joins and filters that are well beyond what you can do in Excel. Still, to my mind, the real strength of Lyza is the ability to create data process flows, which save analysts from trying to do similar work by manually modifying Excel spreadsheets. (Click to read my Lyza review.)

Either way, though, features to document and share analytical processes still matter. Those are really the focus of this white paper, which is written to support the "Lyza Commons” product. Commons lets analysts share their work, trace the origins of each shared item, and use one analysis as input to another. As the paper points out, this both fosters cooperation among analysts and makes it easier for IT to add their activities to the company’s core business intelligence systems. Both benefits should free up analysts’ time for new projects, letting them foxus on what they do best.